[go: up one dir, main page]
More Web Proxy on the site http://driver.im/

Madrero Pardo, 2020 - Google Patents

Creating a model for expected goals in football using qualitative player information

Madrero Pardo, 2020

View PDF
Document ID
2290736577447306444
Author
Madrero Pardo P
Publication year

External Links

Snippet

The field of sports analytics has been growing a lot in recent years. Sports like baseball and basketball were among the first to embrace it, but football has also taken big steps in that direction. One of the causes is that data analysis allows for the development of new …
Continue reading at upcommons.upc.edu (PDF) (other versions)

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62—Methods or arrangements for recognition using electronic means
    • G06K9/6267—Classification techniques
    • G06K9/6279—Classification techniques relating to the number of classes
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62—Methods or arrangements for recognition using electronic means
    • G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/30781—Information retrieval; Database structures therefor; File system structures therefor of video data
    • G06F17/30784—Information retrieval; Database structures therefor; File system structures therefor of video data using features automatically derived from the video content, e.g. descriptors, fingerprints, signatures, genre
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Systems or methods specially adapted for a specific business sector, e.g. utilities or tourism
    • G06Q50/01—Social networking
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00—Subject matter not provided for in other groups of this subclass
    • G06N99/005—Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run

Similar Documents

Publication Publication Date Title
Horvat et al. The use of machine learning in sport outcome prediction: A review
Decroos et al. Actions speak louder than goals: Valuing player actions in soccer
Apostolou et al. Sports Analytics algorithms for performance prediction
Valero Predicting Win-Loss outcomes in MLB regular season games–A comparative study using data mining methods
Pantzalis et al. Sports analytics for football league table and player performance prediction
Eggels et al. Expected goals in soccer: Explaining match results using predictive analytics
Herbinet Predicting football results using machine learning techniques
Thakkar et al. An assessment of football through the lens of data science
Joash Fernandes et al. Predicting plays in the national football league
Decroos Soccer analytics meets artificial intelligence: learning value and style from soccer event stream data
Madrero Pardo Creating a model for expected goals in football using qualitative player information
Kim et al. March Madness prediction: Different machine learning approaches with non‐box score statistics
Anwar et al. Artificial intelligence-driven approach to identify and recommend the winner in a tied event in sports surveillance
Bai et al. What does it take to win or lose a soccer game? A machine learning approach to understand the impact of game and team statistics
Wakelam et al. The collection, analysis and exploitation of footballer attributes: A systematic review
Floyd et al. Shot-by-shot stochastic modeling of individual tennis points
Tripathi et al. Prediction of IPL matches using Machine Learning while tackling ambiguity in results
Liu et al. Insight Analysis for Tennis Strategy and Tactics
Beheshtian-Ardakani et al. CMPN: Modeling and analysis of soccer teams using Complex Multiplex Passing Network
Kerr Applying machine learning to event data in soccer
Chazan-Pantzalis Sports Analytics Algorithms for Performance Prediction
Ouyang et al. Integration of machine learning XGBoost and SHAP models for NBA game outcome prediction and quantitative analysis methodology
Sjöberg Football Match Prediction Using Machine Learning
Papageorgiou Data mining in sports: Daily NBA player performance prediction
Duarte Utilizing machine learning techniques in football prediction